Genotype and treatment biases in estimation of carcass lean of swine.

Carcasses of 181 barrows, representing five genotypes, 1) H x HD, 2) SYN, 3) HD x L[YD], 4) L x YD, and 5) Y x L (H = Hampshire, D = Duroc, SYN = synthetic terminal sire line, L = Landrace, and Y = Yorkshire), and two levels of ractopamine (RAC) treatment (0 and 20 ppm) were completely dissected and the data were used to examine genotype and treatment (RAC) biases in estimation of fat-standardized lean weight and to evaluate accuracies and precisions realized by use of equations based on variables derived from different technologies. Independent variables used to establish regression equations represented technologies of direct carcass measurements, optical probe data, TOBEC (total body electrical conductivity) readings, and dissected (DHMLN) and fat-standardized (FSHMLN) ham lean. Genotype bias existed when any equation from a single technology was used and was minimized by combining FSHMLN with one TOBEC reading, carcass length, and the probe measurement of 10th rib fat depth. Large RAC biases appeared when equations from direct carcass measurements or optical probe data were used and were minimized by an equation using either DHMLN or FSHMLN. A practical equation with relatively high R2 value and small genotype and RAC biases were developed by combining TOBEC readings with direct carcass measurements of 10th rib fat depth and warm carcass weight.     

Using current on-line carcass evaluation parameters to estimate boneless and bone-in pork carcass yield as influenced by trim level.

The objective of this study was to develop prediction equations for estimating proportional carcass yield to a variety of external trim levels and bone-in and boneless pork primal cuts. Two hundred pork carcasses were selected from six U.S. pork processing plants and represented USDA carcass grades (25% USDA #1, 36% USDA #2, 25% USDA #3, and 14% USDA #4). Carcasses were measured (prerigor and after a 24 h chill) for fat and muscle depth at the last rib (LR) and between the third and fourth from last rib (TH) with a Hennessy optical grading probe (OGP). Carcasses were shipped to Texas A&M University, where one was randomly assigned for fabrication. Selected sides were fabricated to four lean cuts (ham, loin, Boston butt, and picnic shoulder) then fabricated progressively into bone-in (BI) and boneless (BL) four lean cuts (FLC) trimmed to .64, .32, and 0 cm of s.c. fat, and BL 0 cm trim, seam fat removed, four lean cuts (BLS-OFLC). Total dissected carcass lean was used to calculate the percentage of total carcass lean (PLEAN). Lean tissue subsamples were collected for chemical fat-free analysis and percentage carcass fat-free lean (FFLEAN) was determined. Longissimus muscle area and fat depth also were collected at the 10th and 11th rib interface during fabrication. Regression equations were developed from linear carcass and OGP measurements predicting FLC of each fabrication point. Loin muscle and fat depths from the OPG obtained on warm, prerigor carcasses at the TH interface were more accurate predictors of fabrication end points than warm carcass probe depth obtained at the last rib or either of the chilled carcass probe sites (probed at TH or LR). Fat and loin muscle depth obtained via OGP explained 46.7, 52.6, and 57.1% (residual mean square error [RMSE] = 3.30, 3.19, and 3.04%) of the variation in the percentage of BI-FLC trimmed to .64, .32, and 0 cm of s.c. fat, respectively, and 49.0, 53.9, and 60.7% (RMSE = 2.91, 2.81, and 2.69%) of the variation in the percentage of BL-FLC trimmed to .64, .32, and 0 cm of s.c. fat, respectively. Fat and loin muscle depth from warm carcass OGP probes at the TH interface accounted for 62.4 and 63.5% (RMSE = 3.38 and 3.27%) of the variation in PLEAN and FFLEAN, respectively. These equations provide an opportunity to estimate pork carcass yield for a variety of procurement end point equations using existing on-line techniques.     

Evaluation of the E+V video image analysis system as a predictor of pork carcass meat yield

This study was conducted to assess the ability of the VCS2001 (E+V, Oranienburg, Germany) video image analysis system to predict pork carcass composition. Pork carcasses (n = 278) were selected from a commercial packing plant to differ in weight, Fat-O-Meater (FOM) predicted percentage lean, and gender. Carcasses were imaged three times with the VCS2001, chilled overnight, and then sequentially fabricated into boneless subprimals. The VCS2001 accurately predicted the weight of total saleable product (R2 = 0.88, root mean square error [RMSE] = 1.84) and fat-corrected lean (R2 = 0.92, RMSE = 1.66), but autocorrelation existed between dependent and independent variables. The VCS2001 was acceptably accurate and precise in predicting weights of bone-in ham (R2 = 0.83, RMSE = 0.80), bone-in loin (R2 = 0.74, RMSE = 1.17), loin lean (R2 = 0.77, RMSE = 0.82), belly (R2 = 0.78, RMSE = 0.94), sparerib (R2 = 0.55, RMSE = 0.28), and boneless shoulder (R2 = 0.73, RMSE = 0.79). Weights were more accurately predicted than yields (as a percentage of hot carcass weight) of total saleable product (R2 = 0.47, RMSE = 1.97) or total fat-corrected lean (R2 = 0.44, RMSE = 1.89) using VCS2002, and it did not accurately predict percentages of bone-in ham (R2 = 0.45, RMSE = 1.13), ham lean (R2 = 0.32, RMSE = 1.46), bone-in loin (R2 = 0.29, RMSE = 1.36), loin lean (R2 = 0.56, RMSE = 0.90), belly (R2 = 0.43, RMSE = 1.08), sparerib (R2 = 0.08, RMSE = 0.32), or boneless shoulder (R2 = 0.30, RMSE = 0.88). New prediction models and equations were developed using VCS2001 output variables plus hot carcass weight to predict weight of total saleable product (R2 = 0.89, RMSE = 1.72) and fat-corrected lean (R2 = 0.93, RMSE = 1.55) with very minimal increases in accuracy and precision over that achieved using E+V-programmed models and equations. Use of new prediction models and equations marginally improved accuracy and precision of estimations of total saleable product yield (R2 = 0.56, RMSE = 1.81) and fat-corrected lean yield (R2 = 0.57, RMSE = 1.67) over that achieved using E+V-programmed models and equations. The VCS2001 was not able to predict pork carcass composition more accurately than existing technology; therefore, further development is needed to assure commercial viability of this instrument.     

Total body electrical conductivity (TOBEC) measurement of compositional differences in hams, loins, and bellies from conjugated linoleic acid (CLA)-fed stress-genotype pigs.

This study was designed to observe the effects of conjugated linoleic acid (CLA) supplementation on lean content of pork carcass primal cuts (hams, loins, and bellies) and to determine the ability of total body electrical conductivity (TOBEC) to predict lean content. A total of 64 crossbred growing-finishing barrows were placed on a control (soybean oil) or CLA (0.75%) diet at an average weight of 40 kg. Pigs were penned in pairs according to diet and stress genotype (negative, carrier, and positive) and slaughtered at 115 kg. Stress genotype was included because of known variations in lean content. Hams (IMPS 401A; n = 64), loins (IMPS 410; n = 24), and bellies (IMPS 408; n = 63) were fabricated from carcasses at 24 h postmortem and scanned for electromagnetic (EM) absorption by a MQ-25 EM scanner. Each wholesale cut was scanned in triplicate at 2.5 MHz to yield a peak mean average (PMA) value then separated into lean, fat, bone, and skin components. Bellies were skinned prior to scanning then subjected to a belly bar firmness test before dissection. Supplementation with CLA had no effect (P > 0.05) on lean ham composition. Regression analysis was used for lean weight prediction using primal weight and PMA value as predictors. Lean content prediction of hams by TOBEC resulted in an R2 of 0.80. Loins from CLA-supplemented pigs exhibited increased lean weight (P < 0.05) and PMA values (P < 0.05) compared to controls. Lean prediction of loins by TOBEC resulted in an R2 of 0.66. Bellies from CLA-supplemented pigs had a higher percentage of moisture (P < 0.03) and protein (P < 0.01) and decreased percentage of lipid (P < 0.01). The R2 values from the regression analysis predicting protein, moisture, protein + moisture, and fat-free soft tissue composition of the skinless bellies were 0.67, 0.68, 0.71, and 0.78, respectively.     

Evaluation of procedures to predict fat-free lean in swine carcasses

The objectives were to develop equations for predicting fat-free lean in swine carcasses and to estimate the prediction bias that was due to genetic group, sex, and dietary lysine level. Barrows and gilts (n = 1,024) from four projects conducted by the National Pork Board were evaluated by six procedures, and their carcass fat-free lean was determined. Pigs of 16 genetic groups were fed within weight groups one of four dietary regimens that differed by 0.45% in lysine content and slaughtered at weights between 89 and 163 kg. Variables in equations included carcass weight and measures of backfat depth and LM. Fat-free lean was predicted from measures of fat and muscle depth measured with the Fat-O-Meater (FOM), Automated Ultrasonic System (AUS), and Ultrafom (UFOM) instruments, carcass 10th-rib backfat and LM area (C10R), carcass last-rib backfat (CLR), and live animal scan of backfat depth and LM area with an Aloka 500 instrument (SCAN). Equations for C10R (residual standard deviation, RSD = 2.93 kg) and SCAN (RSD = 3.06 kg) were the most precise. The RSD for AUS, FOM, and UFOM equations were 3.46, 3.57, and 3.62 kg, respectively. The least precise equation was CLR, for which the RSD was 4.04 kg. All procedures produced biased predictions for some genetic groups (P < 0.01). Fat-free lean tended to be overestimated in fatter groups and underestimated in leaner ones. The CLR, FOM, and AUS procedures overestimated fat-free lean in barrows and underestimated it in gilts (P < 0.01), but other procedures were not biased by sex. Bias due to dietary lysine level was assessed for the C10R, CLR, FOM, and SCAN procedures, and fat-free lean in pigs fed the lowlysine dietary regimen was overestimated by CLR, FOM, and SCAN (P < 0.05). Positive regressions of residuals (measured fat-free lean minus predicted fat-free lean) on measured fat-free lean were found for each procedure, ranging from 0.204+/-0.013 kg/kg for C10R to 0.605+/-0.049 kg/kg for UFOM, indicating that all procedures overestimated fat-free lean in fat pigs and underestimated it in lean pigs. The pigs evaluated represent the range of variation in pigs delivered to packing plants, and thus the prediction equations should have broad application within the industry. Buying systems that base fat-free lean predictions on measures of carcass fat depth and muscle depth or area will overvalue fat pigs and undervalue lean pigs.     

Growth, development, and carcass composition in five genotypes of swine.

An experiment with 127 barrows representing five genotypes, 1) H x HD, 2) SYN, 3) HD x L[YD], 4) L x YD, and 5) Y x L (H = Hampshire, D = Duroc, SYN = synthetic terminal sire line, L = Landrace, and Y = Yorkshire), was conducted to evaluate growth and development of swine from 59 to 127 kg live weight. Animals were allowed ad libitum access to a pelleted finishing diet containing 18.5% CP, .95% lysine, and 10.5% fat, with an energy density of 3,594 kcal of ME/kg. Pigs were serially slaughtered at either 59, 100, 114, or 127 kg live BW. After slaughter, carcasses were chilled and backfat was measured at four locations. The right side of each carcass was fabricated into primal cuts of ham, loin, Boston Butt, picnic, and belly. Composition of each primal cut was determined by physical dissection into lean, fat, bone, and skin. Estimated allometric growth coefficients for carcass length, carcass weight, and longissimus muscle area relative to BW; carcass lean, fat, bone, and skin relative to both BW and carcass weight; and lean in each of the primal cuts relative to total carcass lean did not differ (P greater than .05) among genotypes. Relative to BW, the pooled growth coefficient(s) for carcass weight was (were) greater (P less than .001) than unity, whereas those for carcass length, longissimus muscle area, and backfat at first rib were smaller (P less than .001) than unity. Those for other backfat measurements were close to 1.00. Relative to either BW or carcass weight, the pooled coefficient(s) for fat was (were) greater (P less than .001) than unity, whereas those for lean, bone, and skin were smaller (P less than .001) than unity. Growth of lean, backfat, bone, and skin in the carcass were nearly linearly associated with increases in BW. The increase in fat weight was curvilinear as the pig grew and was accelerated in later growth stages, indicating that carcass fat percentage increased with increased BW.     

Body composition analysis of the pig by magnetic resonance imaging

Magnetic resonance imaging (MRI) was used to measure, in vivo, the volume of several organs and tissues of a total of 111 pigs (males and females) ranging in BW from 6.1 to 97.2 kg. In one experiment the in vivo MRI volumes were compared to tissue or organ weights obtained by dissection. For internal organs, the correlation (R2) between MRI volume and dissected weight ranged from 0.64 (SE of estimation = 65 g) for the heart to 0.90 (SE of estimation = 125 g) for the liver. The MRI volume of the kidneys was approximately 10% less than the dissected weight, whereas the MRI volumes of the heart, liver, and brain exceeded the weights of dissected organs by 13, 17, and 26%, respectively. For fat and muscle tissues, the correlation between MRI volume and dissected weight ranged from 0.82 (psoas muscle) to 0.97 (total right ham muscles). The MRI volume of the backfat and shoulder muscles exceeded the dissected weights by approximately 2%, whereas the MRI volumes of the ham muscles, jowl fat, longissimus muscle, and psoas muscle were 2, 8, 18 and 20% less than their respective weights. In another series of experiments, MRI volume measurements of fat and muscle regions (Jowl fat, backfat, shoulder muscles, LD muscles, psoas muscles, ham muscles, a 10-cm section of the longissimus muscles and overlying fat, and a 15-cm section of the ham muscles and overlying fat) were evaluated by stepwise regression for the prediction of total body fat, lean, and protein. The best prediction of percentage total body fat was obtained using the fat volume from the 10-cm section of longissimus muscle and the fat:muscle ratio from the 15-cm section of the ham (R2 = 0.9). The best prediction of percentage total body protein was obtained using a combination of the volumes (as a percentage of BW) of jowl fat, backfat, shoulder muscle, and ham muscle (R2 = 0.62). The combination fat volume from the 10-cm section of longissimus muscle, the fat:muscle ratio from the 15-cm section of the ham, and the lean volume percentage from the 15-cm section of ham provided the best prediction of the percentage of total body lean (R2 = 0.88).     

The prediction of percentage of fat in pork carcasses

Forty-seven market-weight pigs were slaughtered in order to determine percentage of chemical fat and in an attempt to determine an easily obtainable and inexpensive method to predict this value. The hams and 8-9-10 rib loin sections were removed from the left side of each carcass and dissected into subcutaneous and seam fat, individual muscles, skin and bone. Weights and chemical analysis were determined for each component. Numerous weights, measurements and specific gravity were determined on the carcass, ham and loin section of each pig. Percentage of chemical fat of each ham, loin section and carcasses was determined and correlated with the various weights and measurements taken. Stepwise regression was used to develop prediction equations using carcass data, specific gravity, ham or loin measurements or various combinations of these as dependent variables. The single best indicator of the decimal fraction of chemical fat in the pork carcass was determined to be specific gravity of the carcass half, the prediction equation using this variable had an R-square of .64. By adding 10th rib fat thickness to this equation, the R-square increased to .72. The best equation using carcass variables included 10th rib fat and marbling (R-square = .67). The loin section proved to be an accurate indicator of composition; ham measures were not as accurate as specific gravity and carcass measurements for predicting percentage of carcass fat. This research suggests that the percentage of chemical fat in the pork carcass can be predicted by an easy and inexpensive means.     

Effects of ractopamine on genetically obese and lean pigs

Twenty-eight genetically obese and 24 lean barrows (65.0 and 68.7 kg average BW, respectively) were allotted within genotype to a 16% CP corn-soybean meal basal diet or this basal diet + 20 ppm ractopamine (a phenethanolamine beta-adrenergic agonist) and allowed ad libitum access to feed for 48 d. Compared to lean pigs, obese pigs had lower ADG, gain to feed ratio, longissimus muscle area, predicted amount of muscle, and weights of trimmed loin and ham, ham lean, heart, spleen, kidney and gastrointestinal tract (P less than .05). Obese pigs also had shorter carcass but higher dressing percentage, backfat thickness, fat depth, fat area, untrimmed loin weight and fasting plasma urea N concentration (P less than .05). Dietary supplementation with 20 ppm ractopamine reduced daily feed intake and improved gain to feed ratio in both lean and obese pigs (P less than .05). Pigs fed ractopamine had shorter carcasses, less fat depth and fat area, smaller weights of stomach and colon plus rectum, but higher dressing percentages, longissimus muscle areas, weights of trimmed Boston butts, picnics and loins, ham lean and predicted amounts of muscle than pigs not fed ractopamine (P less than .05). Supplemental ractopamine had no effect on fasting plasma concentrations of urea N, nonesterified fatty acids, triglyceride or glucose (P greater than .05). No genotype x ractopamine interactions for the criteria described above were detected (P greater than .05). These results suggest that ractopamine will improve the efficiency of feed utilization and carcass leanness in swine with different propensities for body fat deposition.     

Genetic correlation between boars, barrows and gilts for various carcass traits

Data from 11 generations of a selection study were analyzed to estimate genetic correlations between boars and gilts, boars and barrows, and gilts and barrows for carcass traits in the Lacombe and Yorkshire breeds of swine. Genetic correlations were estimated to determine if genotype X sex interactions existed and to assess the need for separate genetic parameters for boars and gilts in selection response equations. Genotype X sex interactions were found for total carcass fat/kg of cold carcass weight, area of lean in the ham face/kg of cold carcass weight and percent lean in the ham face/kg of cold carcass weight. Carcass length, longissimus muscle area/kg of cold carcass weight percent ham of side and percent lean in the ham face did not have genotype X sex interactions. Selection based on pooled genetic parameters over sex were favored over selection based on separate genetic parameters regardless of the presence or absence of genotype X sex interactions.     

Carcass traits, cut yields, and compositional end points in high-lean-yielding pork carcasses: effects of 10th rib backfat and loin eye area

Pork carcasses (n = 133) were used to investigate the influence of carcass fatness and muscling on composition and yields of pork primal and subprimal cuts fabricated to varying levels of s.c. fat. Carcasses were selected from commercial packing plants in the southeastern United States, using a 3 x 3 factorial arrangement with three levels of 10th rib backfat depth (< 2.03, 2.03 to 2.54, and > 2.54 cm) and three levels of loin eye area (LEA; < 35.5, 35.5 to 41.9, and > 41.9 cm2). Sides from the selected carcasses were shipped to the University of Georgia for carcass data collection by trained USDA-AMS and University of Georgia personnel and fabrication. Sides were fabricated to four lean cuts (picnic shoulder, Boston butt, loin, and ham) and the skinned belly. The four lean cuts were further fabricated into boneless cuts with s.c. fat trim levels of 0.64, 0.32, and 0 cm. The percentages of four lean cuts, boneless cuts (four lean cuts plus skinned, trimmed belly) at 0.64, 0.32, and 0 cm s.c. fat, fat-free lean, and total fat were calculated. Data were analyzed using a least squares fixed effects model, with the main effects of 10th rib backfat and LEA and their interaction. Fatness and muscling traits increased (P < 0.05) as 10th rib backfat and LEA category increased, respectively. However, fat depth measures were not affected greatly by LEA category, nor were muscling measures greatly affected by backfat category. The percentage yield of cuts decreased (P < 0.05) as backfat category increased. Cut yields from the picnic shoulder, Boston butt, and belly were not affected (P > 0.05) by LEA category, whereas the yield of boneless loin and ham increased (P < 0.05) as LEA category increased. Compositionally, the percentage of four lean cuts, boneless cuts at varying trim levels, and fat-free lean decreased incrementally (P < 0.05) as backfat depth increased, whereas parentage total fat and USDA grade increased (P < 0.05) as backfat depth increased. As LEA increased, percentage boneless cuts trimmed to 0.32 and 0 cm s.c. fat and fat-free lean increased and total fat decreased; however, the difference was only significant in the smallest LEA category. Collectively, these data show that decreased carcass fatness plays a greater role in increasing primal and subprimal cut yields and carcass composition than muscling even in lean, heavily muscled carcasses.     

Tissue weights and body composition of two genetic lines of barrows and gilts from twenty to one hundred twenty-five kilograms of body weight

Barrows and gilts of 2 genetic lines with differing lean gain potentials (high-lean = 375 g of fat-free lean/d; low-lean = 280 g of fat-free lean/d) were used to determine tissue and organ weights and compositions from 20 to 125 kg of BW. The experiment was a 2 (genetic line) x 2 (sex) x 5 (BW) factorial arrangement of treatments in a completely randomized design conducted with 2 groups of pigs in 6 replicates (n = 120 pigs). Six pigs from each sex and genetic line were slaughtered at 20 kg of BW and at 25 kg of BW intervals to 125 kg of BW. At slaughter, the internal tissues and organs were weighed. Loin and ham muscles were dissected from the carcass and trimmed of skin and external fat, and the ham was deboned. Residuals from the loin and ham were combined with the remaining carcass. Body components were ground, and their compositions were determined. The results demonstrated that tissue weights increased (P < 0.01) as BW increased. Loin and ham muscle weights increased but at a greater rate in the high-lean line and in gilts resulting in genetic line x BW and sex x BW interactions (P < 0.01). Liver and heart expressed on a BW or a percentage of empty BW basis increased at a greater rate in the high-lean line resulting in a genetic line x BW interaction (P < 0.01). Liver and intestinal tract weights were heavier in barrows than in gilts, significant only at 45 (P < 0.05), 75 (P < 0.01), and 100 (P < 0.05) kg of BW. Loin and ham muscles from the high-lean genetic line and gilts had greater (P < 0.01) water, protein, and ash contents compared with the low-lean genetic line and barrows resulting in genetic line x BW and sex x BW interactions (P < 0.01). The remaining carcass (minus loin and ham muscles) had greater (P < 0.01) amounts of water and protein, and less (P < 0.01) fat in the high-lean genetic line and gilts. The high-lean genetic line and gilts had more total body water, protein, and ash, but less body fat, with these differences diverging as BW increased, resulting in a genetic line x BW interaction (P < 0.01). The results indicated that liver and heart weights were greater in high-lean pigs, reflecting the greater amino acid metabolism, whereas the liver and intestinal tract weights were greater in barrow than gilts, reflecting their greater feed intakes and metabolism of total nutrients consumed.     

Effects of dietary soy isoflavones on growth, carcass traits, and meat quality in growing-finishing pigs

Two experiments were conducted to determine the effect of soy isoflavones on growth, meat quality, and carcass traits of growing-finishing pigs. In Exp. 1, 36 barrows (initial and final BW, 26 and 113 kg, respectively) were used and each treatment was replicated four times with three pigs each. The dietary treatments were 1) corn-soybean meal (C-SBM), 2) corn-soy protein concentrate (low isoflavones, C-SPC), or 3) C-SPC + isoflavones (isoflavone levels equal to those in C-SBM). Daily gain and ADFI were increased (P < 0.10) in pigs fed the C-SPC relative to pigs fed the C-SPC + isoflavone diet in the late finishing period; otherwise, growth performance was not affected (P > 0.10) by diet. Longissimus muscle area, 10th-rib fat depth, percentage muscling (National Pork Producers Council), 24-h pH and temperature, color, firmness-wetness, marbling, drip loss, and CIE L*, a*, and b* color values were not affected (P > 0.10) by diet. Dressing percentage, carcass length, weight and percentage of fat-free lean in ham and carcass, lean gain per day, lean:fat, and ham weight were increased (P < 0.10), and ham fat and percentage fat in ham and carcass were decreased (P < 0.10) in pigs fed the C-SPC + isoflavone diet compared with pigs fed the C-SPC diet. Pigs fed the C-SPC + isoflavone diet had similar (P > 0.10) carcass traits as pigs fed the C-SBM diet, except carcass length, percentage ham lean and thaw loss were greater (P < 0.10), and total ham fat was less (P < 0.10) in pigs fed the C-SPC + isoflavone diet. In Exp. 2, 60 gilts (initial and final BW, 31 and 116 kg, respectively) were used, and each treatment was replicated five times with four pigs per replicate. The treatments were 1) C-SBM, 2) C-SBM + isoflavone levels two times those in C-SBM, and 3) C-SBM + isoflavone levels five times those in C-SBM. Daily feed intake was linearly decreased (P < 0.10) in the growing phase and increased (P < 0.10) in the late finishing phases as isoflavone levels increased; otherwise, growth performance was not affected (P > 0.10) by diet. Diet did not affect (P > 0.10) carcass traits; however, CIE a* and b* color scores and drip loss were decreased (P < 0.06) as isoflavone levels increased. Soy isoflavones decreased fat and increased lean in barrows when fed within the dietary concentrations found in typical C-SBM diets but not when fed to gilts at concentrations above those present in C-SBM diets.     

Commercial adaptation of ultrasonography to predict pork carcass composition from live animal and carcass measurements.

Live animal and carcass data were collected from market barrows and gilts (n = 120) slaughtered at a regional commercial slaughter facility to develop and test prediction equations to estimate carcass composition from live animal and carcass ultrasonic measurements. Data from 60 animals were used to develop these equations. Best results were obtained in predicting weight and percentage of boneless cuts (ham, loin, and shoulder) and less accuracy was obtained for predicting weight and ratio of trimmed, bone-in cuts. Independent variables analyzed for the live models were live weight, sex, ultrasonic fat at first rib, last rib, and last lumbar vertebra, and muscle depth at last rib. Independent variables for the carcass models included hot carcass weight, sex of carcass, and carcass ultrasonic measurements for fat at the first rib, last rib, last lumbar vertebra, and muscle depth at last rib. Equations were tested against an independent set of experimental animals (n = 60). Equations for predicting weight of lean cuts, boneless lean cuts, fat-standardized lean, and percentage of fat-standardized lean were most accurate from both live animal and carcass measurements with R2 values between .75 and .88. The results from this study, under commercial conditions, suggest that although live animal or carcass weight and sex were the greatest contributors to variation in carcass composition, ultrasonography can be a noninvasive means of differentiating value, especially for fat-standardized lean and weight of boneless cuts.     

Ractopamine treatment biases in the prediction of pork carcass composition

Carcass and live measurements of 45 barrows were used to evaluate the magnitude of ractopamine (RAC) treatment prediction biases for measures of carcass composition. Barrows (body weight = 69.6 kg) were allotted by weight to three dietary treatments and fed to an average body weight of 114 kg. Treatments were: 1) 16% crude protein, 0.82% lysine control diet (CON); 2) control diet + 20 ppm RAC (RAC16); 3) a phase feeding sequence with 20 ppm RAC (RAC-P) consisting of 18% crude protein (1.08% lysine) during wk 1 and 4, 20% crude protein (1.22% lysine) during wk 2 and 3, 16% crude protein (0.94% lysine) during wk 6, and 16% crude protein (0.82% lysine) during wk 6. The four lean cuts from the right side of the carcasses (n = 15/treatment) were dissected into lean and fat tissue. The other cut soft tissue was collected from the jowl, ribs, and belly. Proximate analyses were completed on these three tissue pools and a sample of fat tissue from the other cut soft tissue. Prediction equations were developed for each of five measures of carcass composition: fat-free lean, lipid-free soft tissue, dissected lean in the four lean cuts, total carcass fat tissue, and soft-tissue lipid mass. Ractopamine treatment biases were found for equations in which midline backfat, ribbed carcass, and live ultrasonic measures were used as single technology sets of measurements. Prediction equations from live or carcass measurements underpredicted the lean mass of the RAC-P pigs and underpredicted the lean mass of the CON pigs. Only 20 to 50% of the true difference in fat-free lean mass or lipid-free soft-tissue mass between the control pigs and pigs fed RAC was predicted from equations including standard carcass measurements. The soft-tissue lipid and total carcass fat mass of RAC-P pigs was overpredicted from the carcass and live ultrasound measurements. Prediction equations including standard carcass measurements with dissected ham lean alone or with dissected loin lean reduced the residual standard deviation and magnitude of biases for the three measures of carcass leanmass. Prediction equations including the percentage of lipid of the other cut soft tissue improved residual standard deviation and reduced the magnitude of biases for total carcass fat mass and soft-tissue lipid. Prediction equations for easily obtained carcass or live ultrasound measures will only partially predict the true effect of RAC to increase carcass leanness. Accurate prediction of the carcass composition of RAC-fed pigs requires some partial dissection, chemical analysis, or alternative technologies.     

Predicting tissue distribution and partitioning in terminal sire sheep using x-ray computed tomography

The utility of x-ray computed tomography (CT) scanning in predicting carcass tissue distribution and fat partitioning in vivo in terminal sire sheep was examined using data from 160 lambs representing combinations of 3 breeds (Charollais, Suffolk, and Texel), 3 genetic lines, and both sexes. One-fifth of the lambs were slaughtered at each of 14, 18, and 22 wk of age, and the remaining two-fifths at 26 wk of age. The left side of each carcass was dissected into 8 joints with each joint dissected into fat (intermuscular and subcutaneous), lean, and bone. Chemical fat content of the LM was measured. Tissue distribution was described by proportions of total carcass tissue and lean weight contained within the leg, loin, and shoulder regions of the carcass and within the higher-priced joints. Fat partitioning variables included proportion of total carcass fat contained in the subcutaneous depot and intramuscular fat content of the LM. Before slaughter, all lambs were CT scanned at 7 anatomical positions (ischium, midshaft of femur, hip, second and fifth lumbar vertebrae, sixth and eighth thoracic vertebrae). Areas of fat, lean, and bone (mm(2)) and average fat and lean density (Hounsfield units) were measured from each cross-sectional scan. Areas of intermuscular and subcutaneous fat were measured on 2 scans (ischium and eighth thoracic vertebra). Intramuscular fat content was predicted with moderate accuracy (R(2) = 56.6) using information from only 2 CT scans. Four measures of carcass tissue distribution were predicted with moderate to high accuracy: the proportion of total carcass (R(2) = 54.7) and lean (R(2) = 46.2) weight contained in the higher-priced joints and the proportion of total carcass (R(2) = 77.7) and lean (R(2) = 55.0) weight in the leg region. Including BW in the predictions did not improve their accuracy (P > 0.05). Although breed-line-sex combination significantly affected fit of the regression for some tissue distribution variables, the values predicted were changed only trivially. Within terminal sire type animals, using a common set of prediction equations is justified. Tissue distribution and fat partitioning affect eating satisfaction and efficiency of production and processing; therefore, including such carcass quality measures in selection programs is increasingly important, and CT scanning appears to provide opportunities to do so.     

Practical means for estimating pork carcass composition

Three hundred sixty-one market-weight barrow and gilt carcasses were physically dissected into bone, skin, fat and muscle. A three-variable multiple linear regression equation containing the same independent variables (warm carcass weight, 10th rib loin muscle area and 10th rib fat depth) used (U.S.) to determine pork carcass lean weight was found to be the most practical means for predicting weight of muscle standardized to 10% fat. Multiple linear regression equations containing more than three independent variables produced only slight improvements in R2 values; however, the standard deviation about the regression line was not greatly improved by the addition of more independent variables to this three-independent-variable regression model. A single multiple linear regression equation using the three independent variables above may not be adequate to describe variation over the entire live-weight range for all hogs marketed in the U.S. For most accurate muscle weight prediction, different equations should be used for weight subclasses with one equation for carcasses under 100 kg and another for those heavier than 100 kg. A single prediction equation for muscle weight was adequate for carcasses of both barrows and gilts.     

Effects of betaine on growth, carcass characteristics, pork quality, and plasma metabolites of finishing pigs

An experiment was conducted to determine the effect of dietary betaine (0, 0.125, 0.250, or 0.500%) on growth, carcass traits, pork quality, plasma metabolites, and tissue betaine concentrations of cross-bred finishing pigs. Four replications of three pigs (two barrows and one gilt) each were used for each treatment. The basal diet contained 0.85 (69 to 88 kg BW) or 0.65% Lys (88 to 115 kg BW). Overall ADG and gain:feed were not affected (P > 0.10) by betaine, but overall ADFI was decreased (quadratic, P < 0.05; 0 vs betaine, P < 0.01) by betaine; pigs fed 0.250% betaine had the lowest ADFI. Loin muscle area, average back-fat, dressing percentage, percentage lean, total fat, lean:fat, and leaf fat weight were not affected (P > 0.10) by betaine. Tenth-rib backfat thickness was decreased (quadratic, P < 0.05; 0 vs betaine, P < 0.05); pigs fed 0.250% betaine had the lowest 10th-rib backfat thickness. Carcass length was increased (linear, P < 0.05; 0 vs betaine, P < 0.10) as the level of betaine was increased. Fat-free lean, lean gain per day, ham weight, ham fat-free lean, and ham percentage lean were increased (quadratic, P < 0.10), but percentage fat, total ham fat, percentage ham fat, and butt-fat thickness were decreased (quadratic, P < 0.10); these traits were respectively highest or lowest in pigs fed 0.250% betaine. Thaw loss and 24-h pH were increased (quadratic, P < 0.10; 0 vs betaine, P < 0.05) and cook loss was decreased (linear, P < 0.05) in pigs fed betaine. The CIE L* value for the biceps femoris was decreased (quadratic, P < 0.10; 0 vs betaine, P < 0.10); pigs fed 0.250% betaine had the lowest CIE L* value. Subjective color, firmness-wetness, marbling, percentage moisture and bound water of the loin muscle, and shear force were not affected (P > 0.10) by betaine. Betaine was not detectable (< 0.07 mg/g) in the loin muscle of pigs fed 0% betaine, but betaine was detectable and relatively constant in pigs fed 0.125, 0.250, or 0.500% betaine (0.22, 0.17, and 0.21 mg/g, respectively). Plasma urea N, total protein, albumin, triglycerides, and HDL cholesterol concentrations were not affected (P > 0.10). Plasma total cholesterol (linear, P < 0.10) and NEFA (quadratic, P < 0.10) were increased in pigs fed betaine. Betaine improved carcass traits when provided at 0.250% of the diet and improved some aspects of pork quality.     

Predicting carcass composition of beef cattle using ultrasound technology.

We evaluated 20 slaughtered cattle with ultrasound before hide removal to predict fat thickness and ribeye area at the 12th rib for possible use in carcass composition prediction. Carcasses were fabricated into boneless subprimals that were trimmed progressively from 2.54 to 1.27 to .64 cm maximum fat trim levels. Stepwise regression was used to indicate the relative importance of variables in a model designed to estimate the percentage of boneless subprimals from the carcass at different external fat trim levels. Variables included those obtained on the slaughter floor (ultrasound fat thickness and ribeye area; estimated percentage of kidney, pelvic, and heart [KPH] fat; and warm carcass weight) and those obtained from carcasses following 24 h in the chill cooler (actual fat thickness, actual ribeye area, estimated percentage of KPH fat, warm carcass weight, and marbling score). At all different subprimal trim levels, percentage KPH was the first variable to enter the model. In the models using measures taken on the slaughter floor, ultrasound fat thickness was the only other variable to enter the model. Ultrasound fat thickness increased R2 and decreased residual standard deviation (RSD) in models predicting subprimals at 2.54-cm maximum fat trim; however, at 1.27- and .64-cm trim levels, R2 and RSD increased. Models using the same two variables (except actual fat instead of ultrasound) in the cooler were similar to those using data from the slaughter floor. However, as more cooler measurement variables entered the models, R2 increased and RSD decreased, explaining a greater amount of the variation in the equation. Ultrasonic evaluation on the slaughter floor may be of limited application compared with the greater accuracy found in chilled carcass assessment.     

Evaluation of alternative measures of pork carcass composition

Carcass and live measurements of 203 pigs representing seven genetic populations and four target live weights (100, 114, 128, and 152 kg) were used to evaluate alternative measures of carcass composition. Measures of carcass lean (fat tissue-free lean, FFLM; lipid-free soft tissue, LFSTIS; and dissected lean in the four lean cuts, DL), fat (total carcass fat tissue, TOFAT), and lipid mass (soft tissue lipid, STLIP) were evaluated. Overall, LFSTIS was 22.8% greater than FFLM (47.8 vs 38.9 kg) and TOFAT was 30% greater than STLIP (38.5 vs 29.6 kg). The allometric growth coefficients relative to carcass weight were different for the measures: b = 0.776, 0.828, 0.794, 1.37, and 1.49 for FFLM, LFSTIS, DL, TOFAT, and STLIP, respectively. At 90 kg carcass weight, the predicted growth of FFLM, LFSTIS, TOFAT, and STLIP was 0.314, 0.420, 0.553, and 0.446 kg/kg increase in carcass weight. The difference between FFLM and LFSTIS, representing nonlipid components of the carcass fat tissue, was greater for barrows than for gilts (9.2 vs 8.6 kg). Lipid-free soft tissue mass was predicted more accurately from carcass or live animal measurements than FFLM with smaller relative RSD (4.6 vs 6.5% of their mean values). The alternative measures of carcass composition were evaluated as predictors of empty body protein (MTPRO) and lipid (MTLIP) mass. Empty body protein was predicted with similar accuracy (R2 = 0.74 to 0.81) from either DL, FFLM, LFSTIS, or ribbed carcass measurements. Empty body lipid was predicted more accurately from TOFAT (R2 = 0.92) or STLIP (R2 = 0.93) than ribbed carcass measurements (R2 = 0.88). Although the alternative measures of lean mass (LFSTIS vs FFLM) and lipid mass (TOFAT vs STLIP) were highly related to each other (r = 0.93 to 0.98), they had different relative growth rates (allometric coefficients) and thus cannot be predicted as linear functions of the similar alternative variable without significant weight group biases. From the 100- to 152-kg target weight groups, gilts gained 12.9% greater FFLM and 12.1% greater MTPRO but only 4.4% greater LFSTIS than barrows. Fat-free lean mass is more precise as a measure of muscle growth and as a predictor of lysine requirements. Lipid-free soft tissue can be obtained more quickly and predicted more accurately from carcass or live animal measurements.